Multilayer perceptron architecture optimization using parallel computing techniques
Multilayer perceptron architecture optimization using parallel computing techniques
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Publisher
United States: Public Library of Science
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Language
English
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Publisher
United States: Public Library of Science
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Contents
The objective of this research was to develop a methodology for optimizing multilayer-perceptron-type neural networks by evaluating the effects of three neural architecture parameters, namely, number of hidden layers (HL), neurons per hidden layer (NHL), and activation function type (AF), on the sum of squares error (SSE). The data for the study we...
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Full title
Multilayer perceptron architecture optimization using parallel computing techniques
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TN_cdi_plos_journals_1976410897
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_plos_journals_1976410897
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ISSN
1932-6203
E-ISSN
1932-6203
DOI
10.1371/journal.pone.0189369
